373 citations · 1.3k across the 66 of their papers we have counts for
11 papers · 1 filter
MC-Blur: A Comprehensive Benchmark for Image Deblurring
Kaihao Zhang, Tao Wang, Wenhan Luo +6
Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios. However, in most real-world images, bl…
Dense Uncertainty Estimation
Jing Zhang, Yuchao Dai, Mochu Xiang +7
Deep neural networks can be roughly divided into deterministic neural networks and stochastic neural networks.The former is usually trained to achieve a mapping from input space to…
EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset
Kaihao Zhang, Dongxu Li, Wenhan Luo +4
Recent deep face hallucination methods show stunning performance in super-resolving severely degraded facial images, even surpassing human ability. However, these algorithms are ma…
T-Net: Deep Stacked Scale-Iteration Network for Image Dehazing
Lirong Zheng, Yanshan Li, Kaihao Zhang +1
Hazy images reduce the visibility of the image content, and haze will lead to failure in handling subsequent computer vision tasks. In this paper, we address the problem of image d…
Beyond Monocular Deraining: Parallel Stereo Deraining Network Via Semantic Prior
Kaihao Zhang, Wenhan Luo, Yanjiang Yu +6
Rain is a common natural phenomenon. Taking images in the rain however often results in degraded quality of images, thus compromises the performance of many computer vision systems…
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding
Wenjia Niu, Kaihao Zhang, Wenhan Luo +1
Single-image super-resolution (SR) and multi-frame SR are two ways to super resolve low-resolution images. Single-Image SR generally handles each image independently, but ignores t…
Deep Two-View Structure-from-Motion Revisited
Jianyuan Wang, Yiran Zhong, Yuchao Dai +4
Two-view structure-from-motion (SfM) is the cornerstone of 3D reconstruction and visual SLAM. Existing deep learning-based approaches formulate the problem by either recovering abs…
Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priors
Kaihao Zhang, Rongqing Li, Yanjiang Yu +3
Images captured in snowy days suffer from noticeable degradation of scene visibility, which degenerates the performance of current vision-based intelligent systems. Removing snow f…
ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring
Dongxu Li, Chenchen Xu, Kaihao Zhang +5
Video deblurring models exploit consecutive frames to remove blurs from camera shakes and object motions. In order to utilize neighboring sharp patches, typical methods rely mainly…
Enhanced Spatio-Temporal Interaction Learning for Video Deraining: A Faster and Better Framework
Kaihao Zhang, Dongxu Li, Wenhan Luo +2
Video deraining is an important task in computer vision as the unwanted rain hampers the visibility of videos and deteriorates the robustness of most outdoor vision systems. Despit…
Dual Attention-in-Attention Model for Joint Rain Streak and Raindrop Removal
Kaihao Zhang, Dongxu Li, Wenhan Luo +1
Rain streaks and rain drops are two natural phenomena, which degrade image capture in different ways. Currently, most existing deep deraining networks take them as two distinct pro…